PPTAgent: An Agentic Framework for Reflective PowerPoint Generation

by icip-cas · MCP Server · ★ 5.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Featured in: PPT Skills for Codex & Claude Code

How to install PPTAgent

uvx pptagent onboard
uvx pptagent generate "Single Page with Title: Hello World" -o hello.pptx

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

🧪 Tested by Agent Skills Hub

One of 28 tools we ran end to end on the same task for our PPT Skills for Codex & Claude Code page (2026-10-07).

No. 4 in "The 5 best PPT skills in 2026, by our test".

Result: Ready after touch-ups · Editability L2 · + drawn shapes · content rubric 100% · 4.6 min · added claims not in the brief

What it made in our test

See the slides → · See the whole test →

agentagentic-aillmmcpopenclawpresentationslide

Quick Facts

Stars5,191
Forks617
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score70/100
Open Issues18
Last Updated2026-11-02
Created2025-01-04
Platformsmcp, python
Est. Tokens~17k

About PPTAgent

🌐 Language English | 简体中文 | 繁體中文 | 日本語 | 한국어 | हिन्दी | ไทย | Français | Deutsch | Español | Italiano | Русский | Português

Compatible Skills

These tools work well together with PPTAgent for enhanced workflows:

  • octotools — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
  • PocketFlow — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)
  • ToolOrchestra — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • Hephaestus — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • RagaAI-Catalyst — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (50%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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